This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
Product upvotes vs the next 3
Waiting for data. Loading
Product comments vs the next 3
Waiting for data. Loading
Product upvote speed vs the next 3
Waiting for data. Loading
Product upvotes and comments
Waiting for data. Loading
Product vs the next 3
Loading
Hyerix
AI-native desktop GUI for NATS infrastructure.
A local-first desktop GUI for NATS — streams, consumers, KV buckets, Object Store, cluster topology — without memorizing CLI flags. Signal AI answers cluster questions in plain English ("which consumers are lagging?"), surfaces anomalies before pages fire, and runs root-cause analysis when something looks off. macOS, Windows, Linux. Your NATS data never leaves your machine. 14-day trial, no card.
It's 2am. A consumer is lagging. You're three nats commands deep, piping into jq, trying to remember if it's --last-per-subject or --deliver-last-per-subject.
Hyerix is the GUI that ends that ritual — and ships an AI that tells you which consumer is broken.
The visual layer covers everything you'd otherwise piece together from five CLI commands: stream configs, consumer lag, pending counts, KV buckets, Object Store, server resource usage, cluster topology. One screen, no jq.
The piece I'm most interested in feedback on is Signal AI — a natural-language layer over your live cluster state. You can ask things like:
- "Which consumers have growing pending counts in the orders stream?"
- "Show me streams whose retention policy doesn't match their discard policy.”
and get answers drawn from real cluster data, not training-time docs. It also runs background anomaly detection — for example, flagging a consumer whose ack-pending grew 4× in an hour and pointing at the subject filter that changed — and can do root-cause analysis when something looks off. Your NATS data never leaves your machine. Signal AI runs locally against the cluster state pulled to your desktop. Nothing shipped to a third-party cloud.
Runs on macOS, Windows, and Linux. Built on Tauri v2.
I'm building this for operators running NATS in production. Tell me what's missing.
About Hyerix on Product Hunt
“AI-native desktop GUI for NATS infrastructure.”
Hyerix was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #141 on the daily leaderboard. A local-first desktop GUI for NATS — streams, consumers, KV buckets, Object Store, cluster topology — without memorizing CLI flags. Signal AI answers cluster questions in plain English ("which consumers are lagging?"), surfaces anomalies before pages fire, and runs root-cause analysis when something looks off. macOS, Windows, Linux. Your NATS data never leaves your machine. 14-day trial, no card.
On the analytics side, Hyerix competes within Productivity, Developer Tools and Artificial Intelligence — topics that collectively have 1.6M followers on Product Hunt. The dashboard above tracks how Hyerix performed against the three products that launched closest to it on the same day.
Who hunted Hyerix?
Hyerix was hunted by Hyerix. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Hyerix including community comment highlights and product details, visit the product overview.
Hyerix
It's 2am. A consumer is lagging. You're three nats commands deep, piping into jq, trying to remember if it's --last-per-subject or --deliver-last-per-subject.
Hyerix is the GUI that ends that ritual — and ships an AI that tells you which consumer is broken.
The visual layer covers everything you'd otherwise piece together from five CLI commands: stream configs, consumer lag, pending counts, KV buckets, Object Store, server resource usage, cluster topology. One screen, no jq.
The piece I'm most interested in feedback on is Signal AI — a natural-language layer over your live cluster state. You can ask things like:
- "Which consumers have growing pending counts in the orders stream?"
- "Show me streams whose retention policy doesn't match their discard policy.”
and get answers drawn from real cluster data, not training-time docs. It also runs background anomaly detection — for example, flagging a consumer whose ack-pending grew 4× in an hour and pointing at the subject filter that changed — and can do root-cause analysis when something looks off. Your NATS data never leaves your machine. Signal AI runs locally against the cluster state pulled to your desktop. Nothing shipped to a third-party cloud.
Runs on macOS, Windows, and Linux. Built on Tauri v2.
Try it: hyerix.ai — 14-day trial, no card.
No NATS cluster handy? https://github.com/hyerix/hyerix-demo-cluster spins one up via Docker Compose, pre-loaded with streams, consumers, and synthetic activity.
I'm building this for operators running NATS in production. Tell me what's missing.